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International Journal of Financial
Management (IJFM)
ISSN (P): 2319-491X; ISSN (E): 2319-4928
Vol. 6, Issue 6, Oct– Nov 2017, 1-10
© IASET
Crude Oil Prices and Banks Performance in The Arab Maghreb Countries (Algeria -
Libya - Tunisia - Morocco): Cross Section Analysis
Fatma Bennaceur*
*Lecturer in Finance at Institute of Economics, Commerce and Management Sciences.
LMELSMC Laboratory University of Ain Temouchent BP 284, Ain Temouchent 46000 –
Algeria; E-mail: fatma03.2007@yahoo.fr
* Corresponding author
Ali BENDOB**
**Ph.D. in Finance and lecturer at Institute of Economics, Commerce and Management
Sciences. LMELSMC Laboratory, University of Ain Temouchent BP 284, Ain Temouchent
46000 – Algeria; E-mail: ali.bendob@cunivaintemouchent.dz
Abstract
In the theoretical background the profitability and performance of banking sector will decrease in oil
exporter countries; if crude prices fall; because these countries will suffer from falling revenues,
unemployment rates rise and economic growth slows.This paper examines the relationship between oil
prices and the performance of banks. Using the regression model with unbalanced panel data analysis
at the level of four Arab Maghreb countries (Algeria - Libya - Tunisia - Morocco) over the period
1997-2013. Our results indicate that there is a negative relationship significant between oil prices and
profitability (NIM, ROAA); and a significant negative relationship between inflation and profitability
(NIM, ROAA)of banking sectors in the Arab Maghreb countries in the study.The relationship between
oil prices and loans is a positive and not significant.There is a relationship between GDP and
profitability (NIM, ROAA) of banking sectors in the Arab Maghreb countries is positive and no
significant. This results not change under the three methods POLS, fixed effects and random effects.
The acceptance of random effects model shows that the relationship varies from one country to
another, due to the different characteristics of each economy and varied under time.
Keywords: Oil prices; Performance of banks; Arab Maghreb countries; oil exporting countries;
Unbalanced Panel data.
JEL Classification : G21, C23, L2
1. Introduction
Crude oil plays an important role in the economy, where all the sectors are correlated to this important
product directly or indirectly, especially the transport sector, industries and other sectors. Oil prices
have volatile significantly over the last ten years, especially after the subprime crisis. We present the
following figure to highlight the West Texas Intermediate (WTI or NYMEX) crude oil prices per
barrel fluctuations. Figure 1. Crude oil prices of 10 year daily historical chart
Source : http://www.macrotrends.net/1369/crude-oil-price-history-chart (10/10/2017)
2
Figure 1 shows that the biggest shocks were after the subprime crisis and after the middle of
2014. Oil prices fell sharply below 50 USA $ after it exceeded 140 USA $ years 2008.This
volatility is due to several factors: wars and political instability in the Middle East, increased
the supply of oil in the global market, declining demand for many developing countries,
etc.(Chengcheng and Bingqing 2015). Oil price volatilities have implications for the country's
economy, depending on the nature of its activity that was an importer or exporter of crude oil
(see Said (2016)). The oil exporter countries suffer from falling revenues if crude prices fall,
unemployment rates rise and economic growth slows, as a result, the profitability and
performance of banking sector will be decreased. The importing and non-oil producing
countries pay a lower cost and thus lower production cost. This decline in costs will have a
positive impact on the economy as unemployment rates decline and economic growth
increases. As a result, the banking sector will increase profitability and performance (see
Hesse & Poghosyan (2016)). Ferrouhi’s (2014) work to analyse the performance of major
Moroccan banks during the period 2001-2011 using CAMEL approach. This study aims to
evaluate Moroccan banks capital adequacy, asset quality, management, earnings and liquidity
and then determine financial performance, operating soundness and regulatory compliance of
Moroccan banks. Without the use of standard techniques, the author applied CAMEL
approach only. Sarra and Naoufel (2014) analyzes the determinants of profitability if sample
of 10 Tunisian banks’ over the period 1999-2010, and use the generalized method of moments
(GMM) was used to generate the results of the econometric estimation of the dynamic panel.
The empirical results indicate that many institutional and structural factors significantly
influence the Tunisian banks profitability. Bendob’s (2015) study examine the relationship
between profitability of commercial banks and two types of factors internal and external, for a
sample of 10 public and private Algerian banks over 1997-2012. We use the regression model
with unbalanced panel data analysis and CAMEL approach. He concludes the management
efficiency and liquidity indicators are positively related with profitability, and the capital
indicator is negatively related with profitability. The assets quality, GDP and inflation have
not any significant effect on profitability of commercial banks in Algeria in the period of
study;
In this research paper, we work to verify whether oil prices effect on the profitability and
performance of banking sector and whether this effect is a positive or negative? Is the nature
of the impact of oil prices different between exporting and importing countries? In order to
test this hypotheses, we use the linear regression model for four countries in the Maghreb
(Algeria - Libya - Tunisia - Morocco) over the period 1997-2013.
Section 2 outlines the Literature review of the oil prices effect on the profitability and
performance of banks. In section 3, we present the method and variables of study. In section
4, we present the results of the linear regression model and analysis of results; we compare the
impact of oil prices different between exporting and importing countries, and in section 5, we
give some conclusions.
2. Literature review
The profitability of banks depends on factors specific to the banking sector and the overall economy,
which have confirmed that credit risk is negatively related to profitability (Bendob (2015), (Miller
and Noulas, 1997) because risk management suffers of a deficit in asset quality which led to a
greater increase in loan amounts in difficulty and which negatively affected profitability. It has given
rise to a mixed relationship between liquidity and profitability (Molyneux and Thornton, 1992 and
Bourke, 1989). The most efficient banks can achieve higher profits (Bourke, 1989; Molyneux and
Thornton, 1992), while the bank's profitability may also be stable (Athanasoglu et al., 2008),
whereas they imply a certain level Concentration and market power in the banking sector, both in the
3
entry and exit markets (Short, 1979, Bourke, 1989, Molyneux and Thornton, 1992 and Flamini
et al., 2009).
On the one hand, macroeconomic researchers have found a link between inflation and interest rates
and profitability (Bourke, 1989; Molyneux and Thornton, 1992) and the business cycle and
performance of the bank ( Demirguc-Kunt and Huizinga, 2000, Bikker and Hu, 2002, and
Flamini and others, 2009). Banks are generally able to adjust interest rates if expected inflation is
increased in order to boost profits. Researchers disagree on this point on the basis of the difference
between commercial and Islamic banks. According to (Čihák and Hesse, 2008), Islamic banks often
tend to be financed by vouchers and deposits compatible with Islamic law. The rise in oil prices is
associated with high cash flows, so there is a positive correlation between oil prices and the
performance of Islamic banks. But, with the fall in oil prices and oil yield, they notice the stoppage of
investments in real estate for traditional banks. They assume that Islamic banks that rely on stable
deposits may experience less risk than Islamic banks, which rely mainly on wholesale financing. We
have reported two previous empirical studies of oil price fluctuations with performance. Domenico’s
(2009) article explored the relationship between oil price shocks and the profitability of banks using
data on 145 Banks in the 11 countries of the oil exporting region for the period 1994 to 2008. The
results indicated that oil price shocks have an indirect effect on the profitability of banks, where it
passes through the variables of the ' Global economy and other institutional variables in each country,
while the direct impact is minimal. It seems that investment banks are the most affected compared to
Islamic and commercial banks. The researchers also highlighted the systemic effects of oil price
shocks on the bank's performance, which confirms its importance for the purpose of macro prudential
management in the countries of the region. Chengcheng and Bingqing’s (2014) paper examined the
analysis of the impact of oil prices on the profitability of banks in Canada. Based on data from 10
public banks in the period 1995-2015, researchers used bank profitability indicators and included
special indicators of private banks as well as macroeconomic factors.
Researchers have identified a positive relationship between oil price and bank profitability in the
first period, but there is no evidence to show that they have a relationship in recent years. The
government Has taken measures of interest to banks to protect them from the risks of oil price
fluctuations.
3. Method
For testing the effect of oil prices on banks performance in the Arab Maghreb countries (Algeria,
Libya, Morocco and Tunisia) during the period 1997 to 2013, we use cross section analysis and the
application on a regression model as follows:
titi
Inf ,ti,3,2ti,1iit +GDP+)log(Brent =Prof
Where:
Profit: the profitability of banks for country i at year t, it is represented by three variables as follows:
NIM : is a net interest margin, ROA: is a return on the assets, LOANS : is a credit offered to the
economy (See Benahmed-Daho, et al. (2015)).
Log (Brenti, t): is a natural logarithm of Brent oil prices for year t.
Inf i, t: is a inflation rate for country i at year t;
Log (GDPi, t) is a natural logarithm for gross domestic product for country i at year t.
Our study includes four countries of the Arab Maghreb, classified according to the English alphabet:
Algeria - Libya - Morocco - Tunisia. For the period of 17 years from 1997 until 2013, we downloaded
the statistics from a site of the International Monetary Fund and the World Bank also from the Federal
Bank of America. In this study, we proposed two hypotheses:
H11: There is a negative and significant relationship between volatilities of oil prices and bank
profitability.
H21: There is a positive and significant relationship between volatilities of oil prices and bank
profitability.
This study used several different models among the models of fixed and random effects on the level of
three models according to (NIM - ROA - LOANS).
4
4. Results
Table 1 below shows that most estimators of the Pooled least squares model are statistically also
significantly different from zero, Fisher's statistic indicates acceptance of this model at the significant
level of 1%. Notes that the oil price has a negative and significant relationship between the oil prices
and NIM. The inflation rate has a negative and significant relationship between the oil prices and NIM
at the level 1%. On the other hand, the return ratio of the ROA assets has a statistically significant
relationship with the price of oil and the gross domestic product at the 1% level. Thus, a positive
relation between ROA and GDP has been indicated and an inverse relationship Between the price of
oil and the return on assets knowing that the inflation rate INF is not meant with ROA. Finally, the
ratio of credits offered to the LOANS economy shows a positive and statistically significant
relationship with BRENT, GDP, INF. For this, it can be concluded that the BRENT oil price indicator
has a relationship with the profitability of the banks which is presented by the three ratios: NIM,
ROAA, and LOANS. But we cannot stop our study at this level. In order to do so, we continued our
study, which this time emphasized the impact of fluctuations in oil prices, taking into account the
characteristic of each country in the sample, given that the latter contains four countries, two of them
are oil exporters while the other two do not rely on this product in their economies. The results are as
follows:
Table 1: Result of estimation by pooled least squared method
Included observations: 17
Cross-sections included: 4
Total pool (unbalanced) observations: 68
Dependent Variable
Model 1
(NIM)
Model 2
(ROAA)
Model 3
(LOANS)
Variable
Coefficient
Coefficient
Coefficient
C
6,0846*
1,6886*
12,6388**
(0,0000)
(0,0000)
(0,0289)
LBRENT
-0,5874*
-0,2531*
0,0127 ns
(0,0047)
(0,0082)
(0,9936)
INF
-0,1653**
-0,0614 ns
1,8982*
(0,0585)
(0,1275)
(0,0064)
GDP
0,0000 ns
0,0000*
0,0000*
(0,6000)
(0,0017)
(0,0000)
Adjusted R-squared
0,1593
0,1511
0,3059
S,E, of regression
1,0683
0,4946
8,3904
Sum squared resid
73,03
15,65
4505,49
Log likelihood
-98,9180
-46,5544
-239,0683
F-statistic
5,2306*
4,9740*
10,8409*
Prob(F-statistic)
0,0027
0,0036
0,0000
Source: Authors. () Prob. ; * Significant at1% level; ** Significant at 5% level; *** Significant
at10% level; ns: Not Significant.
Table 2 shows the estimation results of the fixed effects model, we are seen that the Fisher’s statistic is
significant at the level 1%, for the three indicators (NIM, ROA, LOANS).The fixed effects model is
statistically accepted, the parameters of this method is characterized by a high elasticity price of the
oil price in the first model NIM, it reached -0.858, also we noticed an inverse relationship statistically
signified between the BRENT and NIM at the level 1%, thus a statically unrelated inverse relationship
between the inflation rate and the profitability presented by the NIM indicator, on the other hand, the
GDP ratio is significant at the level 5%, and a relationship indicated with the margin of net interest.
5
The elasticity was low and not significant in the third model as small but significant in the second
model. The principal independent variables are non-significant in the third model; one can refuse this
model in this case. Concerning the indicator of the return on average assets ROAA it is noted that it is
not significant statistically, with the rate of inflation but on the side of the variables BRENT, GDP is
significant at the level 1%. We notice there is a positive relationship between GDP and profitability,
therefore, the third model represented by the LOANS indicator is not significant with any variables so
one can distinguish a negative relation with the price variable of Oil and inflation. Summarizes that the
price of oil has an impact on the asset return ratio and the net interest margin only in this case will
affect the performance of banks, which we confirmed in the previous results of the bank performance
with an inverse way or it decreases the net interest margin and asset returns this confirms the existence
of a surplus of liquidity so the banks will thus lower interest rates to encourage investment credits for
Improve the economy of the country especially the oil exporters. Concerning the countries that this
base in its economy on the stock market as the countries of the GCC evaluation of the performance of
these banks in 2008 (global financial crisis) shows a deterioration in bank profits and a loss of
confidence that is installed on transactions banking in general. We can also talk about exchange rates
because it has been observed that sample countries frequently use the Dollars against their currencies,
whereas the rise in oil prices for the countries exporting this product leads to an increase in the foreign
exchange reserves of one country despite its performance and profitability of banks declines due to
excessive investment without the precaution against the risks caused. In Algeria can be attributed to
the applied policy from the government or to the nature of the banking sector. But for both countries,
Libya and Tunisia can be attributed to external factors such as political instability and the Arab Spring,
which have reversed the situation of the national economy and make the internal market weak also the
emergence of the black market with mismanagement of the economy in general. The Oil can be
considered as a wealth for Tunisia and Morocco of the countries consuming this product, so the rise in
prices will have a negative impact on the national economies and on the performance of these banking
systems, due to the rise in prices of commercial transactions with international countries then this
impact will infect neigh boring countries.
But the results of differential estimates in the effects model are presented in the next step.
Table 2: Result of estimation by Cross section fixed effects method
Included observations: 17
Cross-sections included: 4
Total pool (unbalanced) observations: 68
Dependent Variable
Model 1
(NIM)
Model 2
(ROAA)
Model 3
(LOANS)
Variable
Coefficient
Coefficient
Coefficient
C
6,206*
1,964*
20,718*
(0,000)
(0,000)
(0,000)
LBRENT
-0,858*
-0,449*
-1,408ns
(0,000)
(0,000)
(0,246)
INF
-0,011 ns
-0,034 ns
-0,661 ns
(0,910)
(0,408)
(0,250)
GDP
0,000**
0,000*
0,000 ns
(0,044)
(0,000)
(0,235)
Adjusted R-squared
0,306
0,393
0,669
S,E, of regression
0,970
0,418
5,795
Sum squared resid
57,438
10,672
2048,668
Log likelihood
-90,749
-33,524
-212,273
F-statistic
5,931*
8,226*
23,554*
Prob(F-statistic)
0,000
0,000
0,000
Source: Authors.
6
() Prob. ; * Significant at1% level; ** Significant at 5% level; *** Significant at10% level; ns: Not
Significant.
According to Table 3 below, the first NIM model has a negative relationship between it and the
inflation rate, the oil price, also a positive relationship between NIM and GDP. There is a statistical
significance between NIM and INF, BRENT. there is an absence of significance for GDP. The second
model present the ROA has significance with all independent variables, except that it proves a positive
relationship with the GDP and negative with the BRENT and INF. On the other hand, the third model
indicates a positive and significant relationship between inflation rate but the non-significance for oil
prices, concerning the variables GDP and LOANS are statistically significant and shows a negative
relationship between them. The estimation parameters of the random individual effects model with the
generalized least squares method are flexible and take a value less than the fixed effects model. with
the Within method and is accepted only by the fixed effects method in the first two models, so we can
confirm the hypothesis that indicates a negative effect of oil prices on the performance of the banking
sector in the Maghreb countries.
Table 3: Result of estimation by Cross section random effects method
Included observations: 17
Cross-sections included: 04
Total pool (unbalanced) observations: 68
Dependent Variable
Model 1
(NIM)
Model 2
(ROAA)
Model 3
(LOANS)
Variable
Coefficient
Coefficient
Coefficient
C
6,085*
1,689*
12,639*
(0,000)
(0,000)
(0,002)
LBRENT
-0,587*
-0,253*
0,013 ns
(0,002)
(0,002)
(0,991)
INF
-0,165**
-0,061**
1,898*
(0,038)
(0,073)
(0,000)
GDP
0,000 ns
0,000*
0,000*
(0,564)
(0,000)
(0,000)
Adjusted R-squared
0,159
0,151
0,306
S,E, of regression
1,068
0,495
8,390
F-statistic
5,231*
4,974*
10,841*
Prob(F-statistic)
0,003
0,004
0,000
Source: Authors.
() Prob. ; * Significant at1% level; ** Significant at 5% level; *** Significant at10% level; ns: Not
Significant.
The results of the Hausman’s test below confirmed the dependence on the random effect model and
the acceptance of the first hypothesis H0 which consists of the existence of a negative impact between
the fluctuation of oil prices and the performance of the banks (profitability Banking) for the long term
on the ROA, NIM models but there is a positive relationship between the oil price and the LOANS
model especially in the oil exporting countries over the term.
7
Table 4 : Result of Hausman Test
Test cross-section random effects
Test Summary
Chi-Sq.
Statistic
Chi-
Sq.
d.f.
Prob.
Chi-Sq.
Statistic
Cross-section random
0.000
3
0.999
0.000
Source: Authors.
5. Conclusions
Based on the importance of oil and the effects of its volatilities on bank profits. we test the
relationship between oil prices and banks performance, using the data of the banking sector of
the Arab Maghreb countries (Algeria - Libya - Morocco - Tunisia) over the period 1997 2013.
In the first place, several important empirical studies have been highlighted in the field of
banking performance. Then, we study its relationship with oil prices. We support the
theoretical side by a practical study on the banking sector concerning four countries of the
Maghreb for the period 1997-2013. We found a negative relationship between these two
variables represented by the following three models (return on ROA assets - net interest
margin NIM - loans to the total assets) for the period 1997-2013. The most important results
that have been drawn from this study are:
- There is a negative relationship significant at1% level between oil prices and
profitability (NIM, ROAA) of banking sectors in the Arab Maghreb countries (Algeria -
Libya - Morocco - Tunisia).
- There is a positive relationship not significant between oil prices and loans of banking
sectors in the Arab Maghreb countries (Algeria - Libya - Morocco - Tunisia).
- This results not change under the three methods POLS, fixed effects and random effects.
- There is a negative relationship significant between inflation and profitability (NIM,
ROAA) of banking sectors in the Arab Maghreb countries (Algeria - Libya - Morocco -
Tunisia).
- There is a relationship no significant between GDP and profitability (NIM, ROAA) of
banking sectors in the Arab Maghreb countries (Algeria - Libya - Morocco - Tunisia).
- We accept the random effects model, it shows that the relationship varies from one
country to another, due to the different characteristics of each economy.
Based on previous results, it can be said:
- Accept the H11 hypothesis that recognizes there is a negative and significant relationship
between volatilities of oil prices and bank profitability.
- Reject the H21 hypothesis that recognizes there is a positive and significant relationship
between volatilities of oil prices and bank profitability.
For future research of this subject, we can propose to include the regional dimension MENA
for example, and can be applied other econometric techniques in order to test the relationship
between crude oil and profitability of banks.
8
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